Geology ReportsSearch

USGS · 70240922

An extrapolation method for estimating loads from unmonitored areas using watershed model load ratios

Abstract

It is important to routinely estimate loads from an entire watershed to describe current conditions and evaluate how watershed-wide management efforts have affected the nutrient and sediment export that affect downstream water quality. However, monitoring in most areas, including the Great Lakes watershed, consists of sampling at a limited number of sites that are only periodically used to estimate total watershed loading. Here, we describe a technique to extrapolate loads measured at a limited number of reference sites to the total load from a large watershed using load ratios between monitored sites and unmonitored areas obtained from a watershed model (i.e., model load ratio, MLR, approach). In this study, modeled nonpoint-source load ratios between monitored tributaries (reference sites) and nearby unmonitored areas and point-source delivery factors for all areas were obtained from a Spatially Referenced Regression On Watershed attributes (SPARROW) model and used to extrapolate the measured loads from an ongoing monitoring program (Great Lakes Restoration Initiative Tributary monitoring program) to the entire Great Lakes watershed. The MLR approach incorporates spatial variability in nonpoint- and point-source delivery, watershed characteristics, and hydrology that are often not considered when estimating loads from unmonitored areas, such as using the unit area load (UAL) extrapolation approach. The MLR approach provided smaller watershed loads than the UAL approach because yields from monitored sites, in general, were larger than from unmonitored areas. When both approaches were used to estimate loads at adjacent monitored sites, the MLR approach provided more accurate estimates than the UAL approach.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 39.225454999093614° to 50.67086169175306° latitude; -94.5072888118485° to -74.82814615575299° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dale M. Robertson, David A. Saad, Greg F. Koltun. 2022. An extrapolation method for estimating loads from unmonitored areas using watershed model load ratios. https://doi.org/10.1016/j.jglr.2022.09.002

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Thermal habitat use of lake trout in Lake Erie

Understanding the thermal habitat use of fish populations is vital for effective rehabilitation or management, particularly in the face of climate change, given limited thermal tolerances of some species. In Lake Erie, lake trout ( Salvelinus namaycush ) rehabilitation efforts by means of stocking have been ongoing for four decades. However, high water temperatures and lengthening periods of stratification may be hindering reestablishment efforts by contributing to unfavorable conditions for spawning and natural recruitment. We used acoustic telemetry to quantify weekly temperature occupancy of adult lake trout in Lake Erie and evaluated whether temperature occupancy differed relative to fish total length and sex. We found that lake trout occupied water temperatures similar to temperatures occupied by other Great Lakes lake trout populations during summer stratification. During fall, lake trout in Lake Erie occupied warmer temperatures than Lake Huron populations but similar temperatures to Lake Ontario populations. Occupied temperatures decreased with increasing body size during a 7-week period of mid- to late-summer stratification, but not during early summer or fall. Male and female lake trout did not differ in weekly temperature occupancy during any season. These findings reveal similarities with successfully reproducing populations, which suggest that adult temperature occupancy is unlikely to be a major impediment to natural recruitment in Lake Erie.

Lake Erie

Bayesian hierarchical model of lake whitefish cohort strength from sparse trawl data

Recruitment indices for rare or intermittently recruiting fishes are needed to compare year classes and evaluate recruitment drivers, but sparse trawl data with many zero-catch observations complicate estimation. We used fall bottom trawl data from New York, Pennsylvania, and Ohio surveys in Lake Erie's central and eastern basins to estimate annual relative cohort strength of age-0 lake whitefish ( Coregonus clupeaformis ) from 1992 to 2021 and evaluate whether a Bernoulli-Bernoulli presence-absence model retained enough information for an annual relative cohort strength index compared with a Binomial-Poisson count model. We fixed detection probability at 0.31 in the primary analysis and refit both models using alternative fixed values in sensitivity analyses. Among 2879 tows, 173 were positive and 368 fish were collected, with positive catches ranging from 1 to 20 fish. Annual catch per unit area and both models recovered a similar recruitment pattern, with variable recruitment from 1992 to 2005, little to no recruitment from 2006 to 2014, and renewed recruitment in most years from 2015 to 2021. Cohort rank order was stable across fixed detection values (Spearman r s = 0.996 to 1.000), and annual median estimates maintained high agreement with the primary analysis (Pearson r = 0.966 to 1.000). However, Bernoulli-Bernoulli estimates were not one-to-one with Binomial-Poisson estimates, and relative magnitude depended on assumed detection probability. These results indicate that the Bernoulli-Bernoulli simplification is adequate for recovering cohort strength patterns, but the Binomial-Poisson model is more appropriate for distinguishing relative cohort strength among years.

New York, Ohio, Pennsylvania

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Ohio